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Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for India.
Srivastava, Rachit; Tiwari, A N; Giri, V K.
Afiliação
  • Srivastava R; Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur 273010, Uttar Pradesh, India.
  • Tiwari AN; Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur 273010, Uttar Pradesh, India.
  • Giri VK; Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur 273010, Uttar Pradesh, India.
Heliyon ; 5(10): e02692, 2019 Oct.
Article em En | MEDLINE | ID: mdl-31720460
Solar radiation is a critical requirement for all solar power plants. As it is a time-varying quantity, the power output of any solar power plant is also time variant in nature. Hence, for the prediction of probable electricity generation for a few days in advance, for any solar power plant, forecasting solar radiation a few days into the future is vital. Hourly forecasting for a few days in advance may help a utility or ISO in the bidding process. In this study, 1-day-ahead to 6-day-ahead hourly solar radiation forecasting was been performed using the MARS, CART, M5 and random forest models. The data required for the forecasting were collected from a solar radiation resource setup, commissioned by an autonomous body of the Government of India in Gorakhpur, India. From the results, it was determined that, for the present study, the random forest model provided the best results, whereas the CART model presented the worst results among all four models considered.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies Idioma: En Revista: Heliyon Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Índia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies Idioma: En Revista: Heliyon Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Índia